Instructions to use diffusers/FLUX.1-Depth-dev-nf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers/FLUX.1-Depth-dev-nf4 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers/FLUX.1-Depth-dev-nf4", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 932 Bytes
3558706 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | {
"_class_name": "FluxTransformer2DModel",
"_diffusers_version": "0.32.0.dev0",
"_name_or_path": "black-forest-labs/FLUX.1-Depth-dev",
"attention_head_dim": 128,
"axes_dims_rope": [
16,
56,
56
],
"guidance_embeds": true,
"in_channels": 128,
"joint_attention_dim": 4096,
"num_attention_heads": 24,
"num_layers": 19,
"num_single_layers": 38,
"out_channels": 64,
"patch_size": 1,
"pooled_projection_dim": 768,
"quantization_config": {
"_load_in_4bit": true,
"_load_in_8bit": false,
"bnb_4bit_compute_dtype": "bfloat16",
"bnb_4bit_quant_storage": "uint8",
"bnb_4bit_quant_type": "nf4",
"bnb_4bit_use_double_quant": false,
"llm_int8_enable_fp32_cpu_offload": false,
"llm_int8_has_fp16_weight": false,
"llm_int8_skip_modules": null,
"llm_int8_threshold": 6.0,
"load_in_4bit": true,
"load_in_8bit": false,
"quant_method": "bitsandbytes"
}
}
|